Interestingness ranking of media objects

ABSTRACT

Media objects, such as images or soundtracks, may be ranked according to a new class of metrics known as “interestingness.” These rankings may be based at least in part on the quantity of user-entered metadata concerning the media object, the number of users who have assigned metadata to the media object, access patterns related to the media object, and/or a lapse of time related to the media object.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application claims the benefit of priority to U.S. Application No.60/674,109, filed Apr. 21, 2005, and entitled “GENERATION AND USE OFMETADATA FOR MEDIA OBJECTS,” which is incorporated by reference in itsentirety herein.

This application is a continuation of and claims the benefit of U.S.patent application Ser. No. 11/350,981, filed Feb. 8, 2006, which ishereby incorporated by reference in its entirety.

This application is related to U.S. application Ser. No. 11/350,635,entitled “MEDIA OBJECT METADATA ASSOCIATION AND RANKING,” which isincorporated by reference in its entirety herein.

BACKGROUND OF THE INVENTION

1. Field of the Invention

The present invention generally relates to the organization and displayof media objects, and, more particularly, to a new class of metrics forranking media objects, such as images.

2. Description of the Related Art

Existing web sites allow users to comment upon or review media such asbooks or movies. However, conventional web sites are limited in the typeof information concerning media objects that can be provided eitherdirectly by a user or indirectly through the user's actions, and the useof that information to generate search results.

Search results rely upon rankings of items to determine the mostrelevant items to be presented to the searcher. These rankings may bebased upon criteria such as the number of times a particular item was“clicked on” or viewed by a user. It is desired to make available awider variety of user-derived information concerning media objects, andto develop more relevant rankings for media objects based upon thatinformation.

SUMMARY OF THE INVENTION

Embodiments of the invention may determine an interestingness rank for amedia object based at least in part on the quantity of user-enteredmetadata concerning the media object, the number of users who haveassigned metadata to the media object, an access pattern related to themedia object, and/or a lapse of time related to the media object. Therank may also be based at least in part on the relevance of metadata tothe media object.

The interestingness rank may also be “personalized” to a user. Forexample, the rank may be based at least in part on the identity of arequester of the rank of a media object. The “requester” may expresslyrequest the rank, or take an action, through any access pattern, such asentering a search query, that results in presentation of the mediaobject and computation of the interestingness rank, whether or not therank itself is provided to the requester. In particular, the rank may bebased at least in part upon the relationship between a poster of themedia object and the requester of the rank. The apparatus fordetermining the interestingness rank may be located at a server, andeach user may be associated with a corresponding client. Note that therequester of the rank of a media object need not necessarily be a userwho enters metadata concerning the media object.

The personalized interestingness rank for a media object associated witha user may be based at least in part on the number of media objectscommonly assigned the same type of metadata by the user and therequester of the rank. For example, the rank may be based at least inpart on the number of media objects commonly tagged or designated asfavorites by the user and the requester of the rank. The user may beassociated with the media object by virtue of assigning metadata to themedia object, or posting the media object, for example.

The interestingness rank may also be based at least in part on alocation associated with the media object. Logic for ranking the mediaobject may accept a request for ranking of the media object by a firstuser. The rank may be based at least in part on a location associatedwith a residence of the user associated with the media object, or aresidence of a user having a predefined relationship with the firstuser. Note that for all the embodiments herein, unless otherwiseapparent the user who requests (either explicitly or implicitly, asexplained above) a ranking for a media object, or who posts the mediaobject, need not necessarily be a user who enters metadata concerningthe media object.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 illustrates a client-server system according to an embodiment ofthe present invention.

FIG. 2 is a screenshot illustrating the entry of tag metadata to a mediaobject according to an embodiment of the present invention.

FIG. 3 illustrates adding annotation metadata according to an embodimentof the invention.

FIG. 4 illustrates setting permissions according to an embodiment of theinvention.

DETAILED DESCRIPTION OF THE INVENTION

The following description is presented to enable a person of ordinaryskill in the art to make and use the invention. Descriptions of specificdevices, techniques, and applications are provided only as examples.Various modifications to the examples described herein will be readilyapparent to those of ordinary skill in the art, and the generalprinciples defined herein may be applied to other examples andapplications without departing from the spirit and scope of theinvention. Thus, the present invention is not intended to be limited tothe examples described herein and shown, but is to be accorded the scopeconsistent with the claims.

FIG. 1 illustrates a client-server system according to an embodiment ofthe present invention. A media server according to an embodiment of theinvention may include http web server logic, a scripting engine (such asa PHP scripting engine), a database, and an aggregation engine. Themedia server may communicate with multiple clients over a network, suchas the Internet.

The scripting engine may include authentication logic, upload logic,metadata processing logic, and permissions handling logic. Theauthentication logic authenticates a user signing on to the media serverweb site. The upload logic may be used to upload from the client to theserver data conforming to any media format, e.g., still photograph(e.g., JPEG, TIFF), video (e.g., MPEG, AVI), or audio (e.g., MP3, OGG).The aggregation engine may include a statistics engine and a searchengine. A client for use with the server of the invention may include atypical web browser application. Much of the functionality of theinvention may be observed at www.flickr.com, which is incorporated byreference herein in its entirety.

According to an embodiment of the invention, a user at a client uses abrowser to access the media server, and requests an upload of mediaobjects. In response, the upload logic stores the media objects from theclient into the database. For the sake of convenience, we willfrequently use images as examples of media objects manipulated by thesystem, but those skilled in the art will recognize that the inventionapplies to other media objects, subject to appropriate modifications anduse of other functions where appropriate (e.g., viewing a media objectmay apply to viewing a still or moving image or listening to an audiomedia object, such as a soundtrack).

The metadata processing logic permits the user to enter metadata todescribe each image. (As used herein, “metadata” may refer to onemetadatum or plural metadata.) Referring to FIG. 2, the metadata maytake the form of one or more tags for each image, such as four distincttags entered as one space-delimited list “clouds seagull birds sky” foran image of a flying seagull. Other types of metadata include a title(e.g., “Last gull (for now)”), a description of the image, annotations,and comments. An annotation is a descriptive note displayed directlyover a section of the image being annotated. The annotation may behidden from view until the user passes a cursor over the annotatedsection. Referring to FIG. 3, for example, the user may add anannotation near the seagull's wing such as “Note the sunlight comingthrough the wings.” A comment may be entered in a text input box similarto that used for entering comments on a message board. Multiple commentsfrom any permitted user may be made and displayed for a media object.

Referring to FIG. 4, the permissions logic enables the user to setpermissions concerning who is allowed to view each image. For example,the user may set the permissions to allow access only to the userherself, to a limited group of people, e.g., family and/or friends, orto the public (e.g., the entire user base). In addition, the permissionslogic allows the user to permit others to provide metadata regardingeach image. For example, the user may allow friends and/or family, anyother user, someone from the user's contact list, or no one else, to addtags, comments (e.g., “I like the way the seagull is hovering”), orannotations.

The database enables organization of the media objects in a variety ofways. For example, a user's media objects may be organizedchronologically, allowing the user to search media objects by date. Thisorganization allows presentation of the media objects (e.g.,photographic images, still images used to represent video files, oricons representing audio files) on the user's display along a timelineor in a calendar format (e.g., with a selected image from each daydisplayed at the corresponding date entry). The media objects may bedisplayed according to the date of upload, or the date that the mediaobject was created, pursuant to the user's display format choice.Moreover, the scripting engine allows the display of the media objectsin a slide show format.

For photographs, the date of creation may be based upon device-suppliedmetadata, such as metadata from the camera that took the picture,including metadata regarding aperture, shutter speed and other settings.Such metadata may be extracted, for example, from the EXIF (ExchangeableImage File) header stored inside the uploaded file by many digitalcameras, or the IPTC (International Press Telecommunications Council)header stored inside the uploaded file by many photo management andorganization software packages. The chronological organization ofphotographic images may be referred to as a “photostream.”

The database also permits the user to organize media objects uploaded bythe user into sets identified and described by user-provided setidentifiers and descriptions. Each set of images, for example, isanalogous to a photo album. Each media object may belong to multiplesets. The set identifier and description themselves are also metadata.

In contrast to a set, which includes media objects from just one user,media objects from multiple users may be pooled into a “group” using thedatabase. Each group is identified by a group identifier provided by theuser who establishes the group. The grouping of all groups togetherrepresents all the media objects of a particular type (e.g., images)accessible on the media server hosting the media objects. The groupcreator may set various permission levels for accessing and adding mediaobjects to the group. The permission levels may include, for example,public for the entire user base, or private for friends/family or auser-defined social network. Users permitted access to a group may alsobe permitted to add tags, comments and/or annotations. Similar to thedisplay and organization of an individual user's media objects, thedatabase enables the organization and display of group media objects ina time line or calendar format arranged by date, as well as in slideshow.

The media server may include an RSS feed generator to allow a user tosubscribe to a “feed” of media objects, such as media objects belongingto a particular grouping, or identified by a particular tag, that are,for example, ordered by the date they were posted. (A “grouping” mayrefer to any collection, such as all groups of media objects, a singlegroup of multiple users' media objects, all of an individual user'smedia objects, or a set (i.e., subset) of the individual's mediaobjects.) An RSS reader at the user's client computer may be configuredso that only new media objects posted since the user last accessed themedia objects (e.g., updates) will be presented to the user. Similarly,the reader may be configured so that only the most recent of a string ofcomments relating to a particular media object may be displayed usingthis feature.

The statistics engine generates statistics and other metrics based uponaggregated metadata. In one embodiment, the statistics engine determinesthe popularity of metadata (e.g., tags) within a grouping of mediaobjects over a predetermined time period. For example, the statisticsengine may determine the number of different users that have assigned aparticular tag to one or more media objects within all groups on thesystem, within a single group, or within a set of media objects, overthe last 24 hours. The aggregation engine may determine (and display) ahistogram of the tags, and may determine the most frequently assignedtags (at any point in time or over a predetermined time period) bydetermining those tags either having a frequency exceeding a minimumthreshold frequency or belonging to a predetermined number of the mostpopular tags.

In one embodiment of the invention, a predetermined number of metadata(e.g., tags) or terms within metadata (e.g., terms within comments) mayhave their frequency indicated by the size of the font used to displaythem. For example, the 100 most popular tags within all groups may bearranged on a user's display alphabetically, with increasing popularityindicated by increasing font size.

In another embodiment, the statistics engine may determine the“relatedness” of metadata, i.e., a co-occurrence measure of thefrequency with which a particular metadatum (e.g., tag) (or term withina metadatum (e.g., within a comment)) is assigned to a media objectalong with at least one other particular metadatum (or term within ametadatum). In one embodiment, the co-occurrence measure may determinethe frequency of co-occurrence of metadata of the same type. Forexample, out of all 100 images tagged with the word “Italy,” 50 of thoseimages may also be tagged with “Rome,” 25 tagged with “Venice,” 10 with“Florence,” and 2 with “Sienna.” The co-occurrence index wouldrespectively be 50 for “Italy-Rome,” 25 for “Italy-Venice,” 10 for“Italy-Florence,” and 2 for “Italy-Sienna.” In summary, include locationas subset of tags, Tag MD can include location.

In another embodiment, the relatedness metric may be made user-specific,so that it is a co-occurrence measure of the frequency of the number ofusers who have (e.g., have uploaded, or have in their user account) atleast one media object assigned a particular metadatum (e.g., tag) (orterm within a metadatum (e.g., a comment)) along with at least one otherparticular metadatum (or term within a metadatum). For example, out ofall 100 users that have at least one image tagged with the word “Italy,”50 of those users may have images tagged with “Italy” also tagged with“Rome,” 25 also tagged with “Venice,” 10 with “Florence,” and 2 with“Sienna.” The co-occurrence index would respectively be 50 for“Italy-Rome,” 25 for “Italy-Venice,” 10 for “Italy-Florence,” and 2 for“Italy-Sienna.”

A predefined number of the metadata (e.g., tags) having the highestco-occurrence indices, or those having co-occurrence indices exceeding apredefined threshold, may be displayed to the user as “related” metadata(e.g., tags), with at least one metadatum (e.g., tag) not satisfying thepredefined condition being displayed under “See also.” The predefinedthreshold may be computed as a percentage of the maximum possible valueof the index. All such displayed metadata may act as hyperlinks to allmedia objects assigned the designated metadata. The relatedness measuremay be applied to all “public” media objects (i.e., those available toanyone on the system), or to smaller groupings (such as those within agroup or set).

As part of the relatedness computation, the statistics engine may employa statistical clustering analysis known in the art to determine thestatistical proximity between metadata (e.g., tags), and to group themetadata and associated media objects according to correspondingcluster. For example, out of 10,000 images tagged with the word“Vancouver,” one statistical cluster within a threshold proximity levelmay include images also tagged with “Canada” and “British Columbia.”Another statistical cluster within the threshold proximity may insteadbe tagged with “Washington” and “space needle” along with “Vancouver.”Clustering analysis allows the statistics engine to associate“Vancouver” with both the “Vancouver-Canada” cluster and the“Vancouver-Washington” cluster. The media server may provide for displayto the user the two sets of related tags to indicate they belong todifferent clusters corresponding to different subject matter areas, forexample.

An embodiment of the invention permits a user to determine the relevanceof a tag to a media object, in particular to media objects posted byother users. Relevance-setting icons or other input graphics may bedisplayed next to each tag. For example, the icons may include “+” and“−” buttons to indicate whether the user believes that the tag isrelevant or not relevant, respectively, to the displayed media object.The statistics engine may collect the relevance entries for each mediaobject to determine a relevance metric for the object. For example, themetric may simply be the number of entered “+”s divided by the totalnumber of relevance entries for each media object. The statistics engineassociates each vote with the voting user to prevent “stuffing theballot box,” i.e., the statistics engine avoids counting multiple votesby a single user concerning the relevance of a tag to a media object.

The statistics engine may factor the relevance value into the clusteringanalysis to affect the relatedness metric. For example, a tag that has alow relevance value would be treated as less related to other tagsassociated with the same media objects (i.e., weighted to have a longerstatistical distance).

The metadata processing logic 118 may compute an “interestingness”metric for each media object, according to an embodiment of theinvention. Interestingness may be a function of user actions related toa media object, including, for example, the quantity of user-enteredand/or user-edited metadata and/or access patterns for the mediaobjects. Alternatively or in addition to those factors, interestingnessmay be a function of time, system settings, and/or the relationship ofthe user to the poster of the media object.

Each of the above factors may be clipped by a maximum value set by thesystem designer, which is one way of weighting each factor.Alternatively, or in addition, before any clipping, each factor may bemore directly weighted by a weighting coefficient that multiplies thefactor. In either case, the factors (whether weighted or not) may besummed together to create an interestingness score (i.e., rank). Theweighting and clipping may, of course, be applied at a finer level toeach parameter (described below) contributing to any of these factors.

The interestingness score may be computed for any media object for anygrouping, e.g., from all groups containing the media object, from onegroup containing the media object, from the area of the web siteassociated with the poster of the media object, or from within a set ofthat user's media objects containing the media object being scored, forexample.

The quantity of user-entered metadata may include, for example,parameters such as the number of tags, comments and/or annotationsassigned to the media object, and/or the number of users who have addedthe media object to their favorites/bookmarks. (Adding an audio mediaobject to a user's favorites may include adding the media object to auser's playlist.) Alternatively or in addition to those parameters, thequantity of user-entered metadata may be user-related and include, forexample, the number of users who have added tags, comments and/orannotations to the media object, and/or added the media object to theirfavorites/bookmarks.

Alternatively or in addition to those parameters, the metadataprocessing logic 118 may factor into the interestingness score accesspatterns for the media object, such as the number of viewings (orplaybacks) and/or click throughs of the media object, and/or the numberof users who have viewed (or played back), and/or clicked through themedia object or tags related to the media object. Whether theinterestingness algorithm treats a user's action as a “click through,”or, conversely, a “view” or “viewing” of a media object may depend uponthe route the user took to access the media object, i.e., the accesspattern. For example, a search for images assigned a particular tag mayreturn multiple thumbnail images. The algorithm may treat a user'sclicking on a particular one of those thumbnails as a “click through.”

In contrast, for example, an image emailed to a user from another usermay be considered to be “viewed” by the user. In another example, when auser accesses a group pool of images, the user's browser may present theimages as thumbnails. The user may click on a thumbnail to “view” it.Thus, it can be seen that the identical action of clicking on athumbnail image may be treated as a “view” or a “click through”depending upon the path the user took to reach the image, i.e., theaccess pattern. Based upon psychological insights, marketing research orother factors, the system designer may want to treat certain accesspatterns as indicating a higher degree of user interest than others, andassign such access patterns a higher weight in computing theinterestingness score. As perhaps a more illustrative example, if a userreaches and clicks upon a thumbnail image based upon paying $10.00 toaccess the image, then the system designer is likely to assign such anaccess path a higher weighting coefficient than a free access of animage. Conversely, certain sources of traffic, search terms, tag queriesor other precursors to the display of thumbnail images may be determinedto correlate with a motivation that is inconsistent with a highinterestingness, and thus the system designer is likely to assign suchaccess paths relatively low weighting coefficients.

In addition, the metadata processing logic 118 may factor into the scorethe relationship of the poster of the media object to the user (e.g., auser entering a search query). A user may be a member of a private group(e.g., friends and family, an interest group, or a social network)allowed access to the poster's media objects, or a user listed in theposter's contact list, for example. Given the potentially higherlikelihood of a similarity of interests between such a user and theposter relative to other users, this relationship may be weighted andsummed into the interestingness score to increase it.

The above functionality is an example of “personalization” of theinterestingness score. In general, the score may be based upon theidentity of the requester of the interestingness score for the mediaobject. (As used herein, reference to the “requester” or to one whorequests an interestingness score or rank of a media object refers toone who explicitly requests the score, or who takes an action throughany access pattern, such as entering a search query, that results inpresentation of the media object along with computation of theinterestingness score by the metadata processing logic 118, whether ornot the score itself is provided to the requester.) In particular, thescore may be based upon the relationship between the poster of the mediaobject and a user requesting the score.

In another embodiment, the personalized score for a media objectassociated with a user may be based upon the number of media objectsassigned the same type of metadata (e.g., tags or favorites) by thatuser and the score requester. The media object may be associated withthe user by, for example, being assigned metadata by a user or posted bythe user. For example, assume that a first user and a second user storein their on-line albums 100 and 200 photo images, respectively. Thesecond user may search for images associated with a particular tag. Thesearch engine 111 may return an image stored in the first user's album.The metadata processing logic 118 may assign to that image a score as anincreasing function of the number of other images in the first andsecond users' albums that have been commonly designated as favorites orcommonly tagged by the first and second users, under the theory thatsuch shared behavior serves as a predictor that the second user may beespecially interested in images in the first user's album that thesecond user has not yet “favorited” or tagged.

In another embodiment, the metadata processing logic 118 may compute theinterestingness score based upon a location associated with the mediaobject and with a user requesting a score for the media object. Forexample, the metadata processing logic 118 may indicate that a mediaobject is more interesting to a particular user if the locationassociated with the media object is associated with a residence of theuser (e.g., near or in the same geographic region as the user'sresidence), associated with a residence of another user having apredefined relationship with the user, such as a friend or familymember, or associated with a location that is itself associated with athreshold number of media objects that have been assigned metadata(e.g., tagged or favorited) by the user.

In the latter case, for example, the metadata processing logic 118 may,for a particular user, positively factor into the interestingness scoreof an image of the Washington Monument the fact that the user hasdesignated as favorites a large number of images associated with theWashington, D.C. area. This assumes that location metadata indicatingthe Washington area has been associated with the image of the Monument,e.g., by the poster of the image or another user entering the locationthrough a tag field or separate “location” field when assigning metadatato the image.

Other interestingness score components may be set by the systemdesigner. For example, some media objects may be treated as undesirablebecause they contain objectionable content such as obscene imagery orpromotions of a competitor's product. The system designer may, forexample, set up the score computation to decrement the thus-faraccumulated score by a predetermined score offset percentage assigned toa media object having a tag or other metadata on a “blacklist.” Becausea media object may be associated with more than one blacklisted tag, thescore offset value may be chosen to be the greatest score offsetassociated with those tags.

Another score component may take time into account. For example, thesystem designer may set up the score computation to decrement thethus-far accumulated score by a predetermined percentage over timestarting at the time the media object was posted. For example, this timedecay may cause the score to decrement by 2% per day from the day ofposting. This and other means may be employed to prevent the occurrenceof “positive feedback loops” where the sorting of media objects byinterestingness itself skews the results, causing those same mediaobjects to be more frequently accessed, thereby unnaturally increasingtheir interestingness scores.

The ultimate interestingness score may be normalized, so that, forexample, the interestingness score always falls between 0 and 100, or 0and 1. One way of achieving normalization is to divide the actual scorevalue by the maximum possible score value.

The search engine 111 allows the user to search media objects in thedatabase according to various metadata. For example, a user may conducta boolean search of tags among all media objects accessible to the user.Alternatively, the user may perform a full-text boolean search of termsin comments, annotations, titles or descriptions. The media objectsaccessible to a user include, for example, public media objects, mediaobjects within a group, media objects for which the user is afriend/family member or member of another private group, all mediaobjects posted by the user, or the user's media objects within auser-defined set.

The media objects returned from a search may be ranked according tointerestingness. For example, the media server may, in one embodiment,provide for display to the searching user only the media objects havingan interestingness score above a predetermined threshold, or apredetermined number of the highest scoring media objects.

In response to a search by tag, for example, the statistics engine 109may determine the tags (or other metadata) that are most highly relatedto the one or more tags (or other metadata) in the search query(according to the relatedness metric). The media server 100 may returnto the user at a client the most highly related tags (or other metadata)along with the retrieved media objects. If the relatedness computationresults in two clusters of related tags (or other metadata), then mediaobjects associated with the two clusters may be ranked (and displayed)in order of interestingness.

In an advertising context, advertisements may be associated with theirown metadata/keywords, such as “Rome Italy hotels tourism travel” for anItalian hotel advertisement. Based upon those related keywords, an adserver 122 may use the relatedness metric and set of related tags orother metadata provided by the media server via the web server 102 todetermine which advertisements sponsoring the web site are associatedwith predefined metadata/keywords that most closely match the set ofrelated tags. (The ad server may be a third-party server on the network112.) The ad server may provide to the user for display the most closelymatching advertisements. For example, the ad server may provide fordisplay at the user's client computer the ad for Italian hotels inconjunction with the display of pictures from the media server having aset of highly related tags “Rome Italy honeymoon.” In this manner, thead server uses the relatedness metric and set of highly related tags toprovide the advertisements most highly related to the displayed mediaobjects.

In another embodiment, in response to a search by tag (or othermetadatum), the statistics engine may also prevent a media objectassigned a tag (or other metadatum) that has a relevance score fallingbelow a relevance threshold from being returned as a search result.

It will be appreciated that the above description for clarity hasdescribed embodiments of the invention with reference to differentfunctional units. However, it will be apparent that any suitabledistribution of functionality between different functional units may beused without detracting from the invention. Hence, references tospecific functional units are only to be seen as references to suitablemeans for providing the described functionality rather than indicativeof a strict logical or physical structure or organization.

The invention can be implemented in any suitable form includinghardware, software, firmware or any combination thereof. Differentaspects of the invention may be implemented at least partly as computersoftware or firmware running on one or more data processors and/ordigital signal processors. The elements and components of an embodimentof the invention may be physically, functionally and logicallyimplemented in any suitable way. Indeed the functionality may beimplemented in a single unit, in a plurality of units or as part ofother functional units. As such, the invention may be implemented in asingle unit or may be physically and functionally distributed betweendifferent units and processors.

Although the present invention has been described in connection withsome embodiments, it is not intended to be limited to the specific formset forth herein. Rather, the scope of the present invention is limitedonly by the claims. Additionally, although a feature may appear to bedescribed in connection with a particular embodiment, one skilled in theart would recognize that various features of the described embodimentsmay be combined in accordance with the invention. Moreover, aspects ofthe invention describe in connection with an embodiment may stand aloneas an invention.

Moreover, it will be appreciated that various modifications andalterations may be made by those skilled in the art without departingfrom the spirit and scope of the invention. The invention is not to belimited by the foregoing illustrative details, but is to be definedaccording to the claims.

What is claimed is:
 1. An apparatus comprising: a processor; a memory;logic stored on said memory and executed by said processor for detectinga user interaction with a posted media object posted on a website by aposting user, the media object comprising metadata assigned to the mediaobject; logic stored on said memory and executed by said processor foridentifying a source of the interaction, the source comprising one of asearch results page, a group pool of media objects, or an email message;logic stored on said memory and executed by said processor forclassifying the user interaction based on the access pattern, theclassifying comprising: classifying a type of the access pattern as aview if the source is identified as a group pool of media objects andthe user interaction is a click of the posted media object, classifyinga type of the access pattern as a click through if the source isidentified as a click of the posted media object displayed on a searchresults page, and classifying a type of the access pattern as a view ifthe source is an email message; logic stored on said memory and executedby said processor for selecting an access pattern weight based on thetype of the access pattern and a plurality of metadata weights based onthe type of metadata assigned to the media object, wherein the accesspattern weight and each of the metadata weights comprise predefinednumerical coefficients; logic stored on said memory and executed by saidprocessor for scoring the media object with an interestingness score,the scoring based in part on the access pattern weight, the metadataweights, and a relationship between the posting user and the useraccessing the posted media object; and logic stored on said memory andexecuted by said processor for retrieving a plurality of responsiveimages in response to a search query, the responsive images includingthe media object; logic stored on said memory and executed by saidprocessor for removing the media object from the responsive images ifthe interestingness score is below a pre-determined threshold; and logicstored on said memory and executed by said processor for causing displayof the media object on the website if the interestingness score is abovethe pre-determined threshold.
 2. The apparatus of claim 1, wherein thelogic for scoring the media object further comprises logic fordetermining a relationship between the posting user and an accessinguser.
 3. The apparatus of claim 2, further comprising logic forincreasing the score associated with the media object based on anidentified similarity of interests between the accessing user and theposting user.
 4. The apparatus of claim 1, wherein the scoring of themedia object is based upon the identity of an accessing user.
 5. Theapparatus of claim 1, wherein the user interaction is a number ofviewings of the media object.
 6. The apparatus of claim 1, wherein theuser interaction is a number of click throughs of the media object. 7.The apparatus of claim 1, wherein the user interaction is entering asearch query.
 8. The apparatus of claim 1, further comprising logic fordetermining a location associated with an accessing user.
 9. Theapparatus of claim 8, further comprising logic for determining alocation associated with another user having a predefined relationshipwith the accessing user.
 10. The apparatus of claim 1, furthercomprising logic for decrementing the score over time.
 11. A methodcomprising: detecting, by a computing device, a user interaction with aposted media object posted on a website by a posting user, the mediaobject comprising metadata assigned to the media object; identifying, bythe computing device, a source of the interaction, the source comprisingone of a search results page, a group pool of media objects, or an emailmessage; classifying, by the computing device, the user interactionbased on the access pattern, the classifying comprising: classifying atype of the access pattern as a view if the source is identified as agroup pool of media objects and the user interaction is a click of theposted media object, classifying a type of the access pattern as a clickthrough if the source is identified as a selection of the posted mediaobject displayed on a search results page, and classifying a type of theaccess pattern as a view if the source is an email message; selecting,by the computing device, an access pattern weight based on the type ofthe access pattern and a plurality of metadata weights based on the typeof metadata assigned to the media object, wherein the access patternweight and each of the metadata weights comprise predefined numericalcoefficients; scoring, by the computing device, the media object with aninterestingness score, the scoring based in part on the access patternweight, the metadata weights, and a relationship between the postinguser and a user of the plurality of users accessing the posted mediaobject, and the relationship between the location associated with themedia object; and retrieving, by the computing device, a plurality ofresponsive images in response to a search query, the responsive imagesincluding the media object; removing, by the computing device, the mediaobject from the responsive images if the interestingness score is belowa pre-determined threshold; and causing, by the computing device,display of the media object on the website to be adjusted based on theinterestingness score if the interestingness score is above thepre-determined threshold.
 12. The method of claim 11, wherein thescoring of the media object further comprises determining a relationshipbetween the posting user and an accessing user.
 13. The method of claim12, further comprising increasing the score associated with the mediaobject based on an identified similarity of interests between theaccessing user and the posting user.
 14. The method of claim 11, whereinthe scoring of the media object is based upon the identity of anaccessing user.
 15. The method of claim 11, wherein the user interactionis a number of viewings of the media object.
 16. The method of claim 11,wherein the user interaction is a number of click throughs of the mediaobject.
 17. The method of claim 11, wherein the user interaction isentering a search query.
 18. The method of claim 11, further comprisingdetermining a location associated with an accessing user.
 19. The methodof claim 18, further comprising determining a location associated withanother user having a predefined relationship with the accessing user.20. The method of claim 11, further comprising decrementing the scoreover time.